The United States Air Force's Focus on AI Research and Development

      In the vast expanse of the digital frontier, where cutting-edge technology meets the demands of modern warfare, the United States Air Force stands at the forefront of innovation. Among its arsenal of advancements, artificial intelligence emerges as a pivotal force, shaping the future of aerial dominance and national security.

  Nestled within the corridors of research institutions and laboratories, the USAF's commitment to AI research and development resonates with an unwavering dedication to staying ahead of the curve. Embarking on a journey fueled by ingenuity and technological prowess, the Air Force charts a course toward enhanced autonomy, operational efficiency and strategic advantage.

  At the heart of this endeavor lies a multifaceted approach, encompassing diverse focus areas that converge to redefine the landscape of aerial warfare. From autonomous systems to predictive analytics, the USAF's pursuit of AI transcends traditional boundaries, ushering in a new era of capabilities and possibilities. 

 Within the realm of strategic intelligence, AI emerges as a force multiplier, augmenting human expertise with unparalleled analytical capabilities. 

  “Artificial intelligence is an evolution of software code that allows us to do things with technology that we haven't been able to do before, just like the computer was able to allow us to make groundbreaking leaps,” said Col. Tucker Hamilton, 96th Operations Group commander at Eglin Air Force Base and Air Force AI test and operations chief.

  Leveraging advanced algorithms and machine learning models, the USAF harnesses the power of data to discern patterns, anticipate threats and inform decision-making processes with unprecedented precision. 

  “In general, when we're talking about artificial intelligence, we're really talking about machine learning. And when we're talking about machine learning, we're talking about the next evolution of software code,” Hamilton said. 

  “We give the software an initial data set with guardrails, but then the software is actually rewriting aspects of it in order to optimize a human-defined objective. It is learning in a mathematical loop process. It's not magic, it's math.”

  Whether assessing geopolitical landscapes or analyzing battlefield dynamics, AI-driven intelligence platforms empower commanders with actionable insights in real-time.

As the demand for autonomous capabilities surges, the USAF spearheads the development of next-generation unmanned aerial vehicles infused with AI intelligence to further the goals of the Collaborative Combat Aircraft program. 

  Enter the X-62 Variable In-Flight Stability Test Aircraft, a bespoke F-16 fighter jet originally used to test what would become the precursor to the F-22 Raptor’s thrust vectoring capability. The aircraft is providing the test bed necessary to make significant leaps toward integrating AI in kinetic systems.

  The goal is to meld the expertise and unmatched skill of U.S. Air Force pilots with the computational reasoning and speed offered by AI, merging a human pilot’s intuition with algorithmic precision to change the face of air combat as we know it.

  “Machine learning is different from more traditional, rules-based coding because rather than using “if-then” statements to make decisions, the machine learning algorithms are using robust statistical methods to discern patterns within massive data sets,” said Col. James Valpiani, the commandant of United States Air Force Test Pilot School at Edwards Air Force Base.

  “The resulting patterns are not easy for humans to read, understand or predict how they'll perform once they're implemented in a real-world environment, and that leads to really hard questions about trust and responsibility, especially in the realm of combat autonomy. But these aren’t just issues that are specific to the Air Force, they apply in everyday life. Autonomous vehicles are using these same machine learning algorithms.”

To address these challenges, Valpiani explained how TPS is using the X-62 to train these algorithms to the same standard every human pilot must meet.

   “A key aspect of our autonomy testing is ensuring that the algorithms we’re working with conform to the expectations of responsible use. There are training rules and expectations of conduct that all human fighter pilots are expected to adhere to, and we work with all of our partners, whether that’s the Air Force Research Laboratory, DARPA or some other entity, to ensure that these concepts are being integrated at every stage of autonomy testing,” Valpiani said. “Then, when we bring them over into real-world application in the X-62 from the simulation environment, we are assessing the same responsibility characteristics to ensure that they behave according to all the same rules that we hold ourselves to as human pilots.” 

  That’s one of the critical advantages of the X-62 Vanguard: its capacity to facilitate safer and more reliable testing environments by including a pilot and engineer in the cockpit, not as operators but as overseers for the AI systems in action. 

  "Having a human on board provides a crucial layer of oversight, allowing us to push the limits of AI with confidence in our ability to intervene if necessary," Valpiani explained. “It allows us to build confidence in these systems not only from the perspective of ‘Are they efficacious? Do they do the mission we set them out to do?’ but also, are they responsible, are they reliable, do they adhere to all the same norms and expectations of responsible use we expect of all humans in these environments?”

  The U.S. Air Force Test Pilot School and the Defense Advanced Research Projects Agency were finalists for the 2023 Robert J. Collier Trophy, a formal acknowledgement of recent breakthroughs in the aerospace industry that have launched the machine-learning era.

  The teams worked together to test breakthrough executions in artificial intelligence algorithms using the X-62A VISTA aircraft as part of DARPA’s Air Combat Evolution (ACE) program.

Also supplying autonomy test data for the development of Collaborative Combat Aircraft will be Project VENOM-AFT at Eglin Air Force Base, Florida. The Viper Experimentation and Next-gen Operations Model – Autonomy Flying Testbed program will be conducted by the 40th Flight Test Squadron and the 85th Test and Evaluation Squadron.

  VENOM is designed and funded to accelerate testing of autonomy software on crewed and un-crewed aircraft. It will complement the ADAx (autonomy data and artificial intelligence experimentation proving ground) at Eglin AFB and inform the CCA program and other autonomy developers. 

  As with the ACE program conducted by the X-62A VISTA, VENOM-AFT will integrate artificial intelligence, machine learning and autonomous systems into modified F-16 platforms. This will allow an onboard pilot to monitor and govern the autonomous systems during testing. The first modified F-16s arrived at Eglin AFB in February 2024.

  “It’s important to understand the ‘human-on-the-loop’ aspect of this type of testing, meaning that a pilot will be involved in the autonomy in real-time and maintain the ability to start and stop specific algorithms,” said Lt. Col. Joe Gagnon, 85th TES commander. “There will never be a time where the VENOM aircraft will solely ‘fly by itself’ without a human component.” 

  Operators will provide feedback during modeling, simulation, and post-flight to the autonomy developers to improve performance over time and ensure the autonomy is making the appropriate decisions prior to and during flight.